With contributions from
This edition first published 2018
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Library of Congress Cataloging‐in‐Publication Data
Names: Chen, Hua‐Peng, author. | Ni, Yi‐Qing, contributor.
Title: Structural health monitoring of large civil engineering structures / by Hua‐Peng Chen ; with contribution from Yi‐Qing Ni.
Description: Hoboken, NJ : John Wiley & Sons, 2018. | Includes index. | Identifiers: LCCN 2017042885 (print) | LCCN 2017056352 (ebook) | ISBN 9781119166627 (pdf) | ISBN 9781119166634 (epub) | ISBN 9781119166436 (cloth)
Subjects: LCSH: Structural health monitoring. | Structural analysis (Engineering)
Classification: LCC TA656.6 (ebook) | LCC TA656.6 .C44 2018 (print) | DDC 624.1/71–dc23
LC record available at https://lccn.loc.gov/2017042885
Cover design: Wiley
Cover image: © ngkaki/Gettyimages
Civil engineering structures such as bridges and buildings are typically large and are built with uncertainties. Their behaviour during the construction phase should be monitored to control the quality and safety of the construction processes. After civil structures have been constructed, the construction materials are subjected to degradation over time, leading to a decrease in structural capacity and serviceability. Monitoring during the service phase offers useful information on structural performance under gradual material degradation and expected loads, and also records the structural responses of unexpected sudden overloading. Data collected from real time monitoring can then be used for damage assessment and health evaluation of the civil engineering structures in service. The continuously measured data from the monitoring system can provide the basis for predicting future performance and determining optimum maintenance strategy for the existing structures.
Structural health monitoring (SHM) is a process of in‐service damage identification and health evaluation for an engineering structure through an automated monitoring system. SHM uses sensing systems and necessary hardware and software facilities to monitor structural responses and operational conditions of the structure. A typical SHM strategy comprises several key components, including sensors, data acquisition, data transmission, data processing, data management, health evaluation and decision making. Sensing technology and the signal interpretation algorithms are two critical factors in developing successful SHM strategies for large civil engineering structures. Damage assessment methods using vibration measurements such as modal parameters show promise for the health evaluation of the civil structures.
The development of a structural health monitoring strategy requires a multidisciplinary approach involving many fields, such as sensors and sensor networks, signal processing, modal testing, numerical modelling, probabilistic analysis, damage diagnosis and damage prognosis. Each of these topics is a discipline‐specific subject by itself, and is equally important in developing effective SHM strategies. Sensing systems are critical for accurate data acquisition and transmission, and the acquired data is used for signal processing to extract key features sensitive to local damage. Modal testing and analysis is adopted to identify modal parameters from vibration measurements, and the obtained modal data can be used for model updating and damage assessment. Probabilistic approaches are needed for numerical modelling to account for uncertainties, and provide an essential framework for reliability analysis and damage prognosis. The objective of this book is to integrate these topics with the specific focus on developing SHM strategies for large civil engineering structures.
This book aims to explain the principles of the SHM strategy, and so it covers all aspects of sensing system, data processing and analysis, damage assessment and decision making for structural monitoring and health evaluation of large civil engineering structures. The book consists of four major parts. First, sensors and sensing technology and data transmission systems are introduced for monitoring of civil structures. From the data measured from the monitoring system on the structure, modal analysis techniques are presented to extract modal parameters, which are used to update and validate the associated finite element numerical model. Then, various methods are provided for identifying the existence, location and extent of damage in civil structures using the measured data and their derivatives. Finally, from the continuously monitored data, probabilistic approaches are utilised for deterioration modelling and reliability analysis, giving the basis for decision making. The techniques for the SHM strategy are well explained in a number of examples and are also demonstrated in many real case studies.
This book can be used as the textbook for a graduate level course on structural health monitoring with emphasis on civil engineering structures. Also, the book can be used as a guide for the practising engineers who want to apply SHM techniques in practice. The book is written with an assumption that the reader has a basic engineering background and needs knowledge of little more than undergraduate level mathematics. Furthermore, the book is an invaluable reference for those undertaking research in the areas of structural monitoring and health evaluation of civil engineering structures.
In this book, several real case studies on health monitoring of civil engineering structures, such as Tsing Ma Bridge, Ting Kau Bridge and Canton Tower, are generously contributed by Professor Yi‐Qing Ni, The Hong Kong Polytechnic University. These practical applications cover various areas in structural health monitoring technology including sensors and sensing networks, data transmission and processing systems, structural damage identification techniques and usage monitoring systems, which are used as examples in several chapters, such as Chapter 2, Chapter 3, Chapter 7 and Chapter 10. The book would not be complete without these practical examples, thus deepest gratitude must go to Professor Yi‐Qing Ni and his colleagues, in particular Professor J.M. Ko, Dr. K.Y. Wong and Dr. X.W. Ye.
Finally, the author is indebted to many people for their direct and indirect assistance in the preparation of this book. The author would like to thank the former and current colleagues, research fellows and PhD students for their support and useful works, particularly Dr. T.L. Huang, Dr. T.S. Maung, Dr. J. Nepal and Mr. C. Zhang. The author deeply thanks his family for their continuous patience and understanding; especially Chengheng Xiao, Helen, Alice and Xuezhang have been the constant supporters.
November 2017
Hua‐Peng Chen, in London
Hua‐Peng Chen is Professor of Civil Engineering, Head of Innovative and Smart Structures at the University of Greenwich, UK. He received his PhD in Structural Engineering from the University of Glasgow, UK. He has been working for over 20 years on structural health monitoring, advanced numerical modelling and structural performance assessment. He is a Chartered Civil Engineer (UK) and a Fellow of the Institution of Civil Engineers (UK).